Rare endocrine diseases are complex conditions that require lifelong specialized care due to their chronic nature and associated long-term complications. In Korea, a lack of nationwide data on clinical practice and outcomes has limited progress in patient care. Therefore, the Multicenter Networks for Ideal Outcomes of Pediatric Rare Endocrine and Metabolic Disease (OUTSPREAD) study was initiated. This study involves 30 centers across Korea. The study aims to improve the long-term prognosis of Korean patients with rare endocrine diseases by collecting comprehensive clinical data, biospecimens, and patient-reported outcomes to identify complications and unmet needs in patient care. Patients with childhood-onset pituitary, adrenal, or gonadal disorders, such as craniopharyngioma, congenital adrenal hyperplasia (CAH), and Turner syndrome were prioritized. The planned enrollment is 1,300 patients during the first study phase (2022–2024). Clinical, biochemical, and imaging data from diagnosis, treatment, and follow-up during 1980–2023 were retrospectively reviewed. For patients who agreed to participate in the prospective cohort, clinical data and biospecimens will be prospectively collected to discover ideal biomarkers that predict the effectiveness of disease control measures and prognosis. Patient-reported outcomes, including quality of life and depression scales, will be evaluated to assess psychosocial outcomes. Additionally, a substudy on CAH patients will develop a steroid hormone profiling method using liquid chromatography-tandem mass spectrometry to improve diagnosis and monitoring of treatment outcomes. This study will address unmet clinical needs by discovering ideal biomarkers, introducing evidence-based treatment guidelines, and ultimately improving long-term outcomes in the areas of rare endocrine and metabolic diseases.

Rare endocrine diseases are complex conditions that require lifelong specialized care due to their chronic nature and associated long-term complications. In Korea, a lack of nationwide data on clinical practice and outcomes has limited progress in patient care. Therefore, the Multicenter Networks for Ideal Outcomes of Pediatric Rare Endocrine and Metabolic Disease (OUTSPREAD) study was initiated. This study involves 30 centers across Korea. The study aims to improve the long-term prognosis of Korean patients with rare endocrine diseases by collecting comprehensive clinical data, biospecimens, and patient-reported outcomes to identify complications and unmet needs in patient care. Patients with childhood-onset pituitary, adrenal, or gonadal disorders, such as craniopharyngioma, congenital adrenal hyperplasia (CAH), and Turner syndrome were prioritized. The planned enrollment is 1,300 patients during the first study phase (2022–2024). Clinical, biochemical, and imaging data from diagnosis, treatment, and follow-up during 1980–2023 were retrospectively reviewed. For patients who agreed to participate in the prospective cohort, clinical data and biospecimens will be prospectively collected to discover ideal biomarkers that predict the effectiveness of disease control measures and prognosis. Patient-reported outcomes, including quality of life and depression scales, will be evaluated to assess psychosocial outcomes. Additionally, a substudy on CAH patients will develop a steroid hormone profiling method using liquid chromatography-tandem mass spectrometry to improve diagnosis and monitoring of treatment outcomes. This study will address unmet clinical needs by discovering ideal biomarkers, introducing evidence-based treatment guidelines, and ultimately improving long-term outcomes in the areas of rare endocrine and metabolic diseases.

Rare endocrine diseases are complex conditions that require lifelong specialized care due to their chronic nature and associated long-term complications. In Korea, a lack of nationwide data on clinical practice and outcomes has limited progress in patient care. Therefore, the Multicenter Networks for Ideal Outcomes of Pediatric Rare Endocrine and Metabolic Disease (OUTSPREAD) study was initiated. This study involves 30 centers across Korea. The study aims to improve the long-term prognosis of Korean patients with rare endocrine diseases by collecting comprehensive clinical data, biospecimens, and patient-reported outcomes to identify complications and unmet needs in patient care. Patients with childhood-onset pituitary, adrenal, or gonadal disorders, such as craniopharyngioma, congenital adrenal hyperplasia (CAH), and Turner syndrome were prioritized. The planned enrollment is 1,300 patients during the first study phase (2022–2024). Clinical, biochemical, and imaging data from diagnosis, treatment, and follow-up during 1980–2023 were retrospectively reviewed. For patients who agreed to participate in the prospective cohort, clinical data and biospecimens will be prospectively collected to discover ideal biomarkers that predict the effectiveness of disease control measures and prognosis. Patient-reported outcomes, including quality of life and depression scales, will be evaluated to assess psychosocial outcomes. Additionally, a substudy on CAH patients will develop a steroid hormone profiling method using liquid chromatography-tandem mass spectrometry to improve diagnosis and monitoring of treatment outcomes. This study will address unmet clinical needs by discovering ideal biomarkers, introducing evidence-based treatment guidelines, and ultimately improving long-term outcomes in the areas of rare endocrine and metabolic diseases.

Purpose: A critical indicator of the overall survival of patients with high-grade glioma is the successful isolation of tumor mesenchymal stem-like cells (tMSLCs), which play important roles in glioma progression. However, attempts to isolate tMSLCs from surgical specimens have not always been successful, and the reasons for this remain unclear. Considering that the amount of surgical high-grade glioma specimens varies, we hypothesized that larger surgical specimens would be better for tMSLC isolation. Materials and Methods: We assessed 51 fresh, high-grade glioma specimens and divided them into two groups according to the success or failure of tMSLC isolation. The success of tMSLC isolation was confirmed by plastic adherence, presenting antigens, tri-lineage differentiation, and non-tumorigenicity. Differences in characteristics between the two groups were tested using independent two sample t-tests, chi-square tests, or Kaplan-Meier survival analysis. Results: The mean specimen weights of the groups differed from each other (tMSLC-negative group: 469.9±341.9 mg, tMSLC positive group: 546.7±618.9 mg), but the difference was not statistically significant. The optimal cut-off value of specimen weight was 180 mg, and the area under the curve value was 0.599. Conclusion Our results suggested a minimum criterion for specimen collection, and found that the specimen amount was not deeply related to tMSLC detection. Collectively, our findings imply that the ability to isolate tMSLCs is determined by factors other than the specimen amount.

Purpose: A critical indicator of the overall survival of patients with high-grade glioma is the successful isolation of tumor mesenchymal stem-like cells (tMSLCs), which play important roles in glioma progression. However, attempts to isolate tMSLCs from surgical specimens have not always been successful, and the reasons for this remain unclear. Considering that the amount of surgical high-grade glioma specimens varies, we hypothesized that larger surgical specimens would be better for tMSLC isolation. Materials and Methods: We assessed 51 fresh, high-grade glioma specimens and divided them into two groups according to the success or failure of tMSLC isolation. The success of tMSLC isolation was confirmed by plastic adherence, presenting antigens, tri-lineage differentiation, and non-tumorigenicity. Differences in characteristics between the two groups were tested using independent two sample t-tests, chi-square tests, or Kaplan-Meier survival analysis. Results: The mean specimen weights of the groups differed from each other (tMSLC-negative group: 469.9±341.9 mg, tMSLC positive group: 546.7±618.9 mg), but the difference was not statistically significant. The optimal cut-off value of specimen weight was 180 mg, and the area under the curve value was 0.599. Conclusion Our results suggested a minimum criterion for specimen collection, and found that the specimen amount was not deeply related to tMSLC detection. Collectively, our findings imply that the ability to isolate tMSLCs is determined by factors other than the specimen amount.

Background: Conventional diagnostic approaches for adrenal tumors require multi-step processes, including imaging studies and dynamic hormone tests. Therefore, this study aimed to discriminate adrenal tumors from a single blood sample based on the combination of liquid chromatography-mass spectrometry (LC-MS) and machine learning algorithms in serum profiling of adrenal steroids. Methods: The LC-MS-based steroid profiling was applied to serum samples obtained from patients with nonfunctioning adenoma (NFA, n=73), Cushing’s syndrome (CS, n=30), and primary aldosteronism (PA, n=40) in a prospective multicenter study of adrenal disease. The decision tree (DT), random forest (RF), and extreme gradient boost (XGBoost) were performed to categorize the subtypes of adrenal tumors. Results: The CS group showed higher serum levels of 11-deoxycortisol than the NFA group, and increased levels of tetrahydrocortisone (THE), 20α-dihydrocortisol, and 6β-hydroxycortisol were found in the PA group. However, the CS group showed lower levels of dehydroepiandrosterone (DHEA) and its sulfate derivative (DHEA-S) than both the NFA and PA groups. Patients with PA expressed higher serum 18-hydroxycortisol and DHEA but lower THE than NFA patients. The balanced accuracies of DT, RF, and XGBoost for classifying each type were 78%, 96%, and 97%, respectively. In receiver operating characteristics (ROC) analysis for CS, XGBoost, and RF showed a significantly greater diagnostic power than the DT. However, in ROC analysis for PA, only RF exhibited better diagnostic performance than DT. Conclusion The combination of LC-MS-based steroid profiling with machine learning algorithms could be a promising one-step diagnostic approach for the classification of adrenal tumor subtypes.

Background: Hereditary hemolytic anemia (HHA) is a rare disease characterized by premature red blood cell (RBC) destruction due to intrinsic RBC defects. The RBC Disorder Working Party of the Korean Society of Hematology established and updated the standard operating procedure for making an accurate diagnosis of HHA since 2007. The aim of this study was to investigate a nationwide epidemiology of Korean HHA. Methods: We collected the data of a newly diagnosed pediatric HHA cohort (2007–2016) and compared this cohort's characteristics with those of a previously surveyed pediatric HHA cohort (1997–2006) in Korea. Each participant's information was retrospectively collected by a questionnaire survey. Results: A total of 369 children with HHA from 38 hospitals distributed in 16 of 17 districts of Korea were investigated. RBC membranopathies, hemoglobinopathies, RBC enzymopathies, and unknown etiologies accounted for 263 (71.3%), 59 (16.0%), 23 (6.2%), and 24 (6.5%) of the cases, respectively. Compared to the cohort from the previous decade, the proportions of hemoglobinopathies and RBC enzymopathies significantly increased (P < 0.001 and P = 0.008, respectively). Twenty-three of the 59 hemoglobinopathy patients had immigrant mothers, mostly from South-East Asia. Conclusion In Korea, thalassemia traits have increased over the past 10 years, reflecting both increased awareness of this disease and increased international marriages. The enhanced recognition of RBC enzymopathies is due to advances in diagnostic technique; however, 6.5% of HHA patients still do not have a clear diagnosis. It is necessary to improve accessibility of diagnosing HHA.

Background: Hodgkin's lymphoma (HL) constitutes 10%–20% of all malignant lymphomas and has a high cure rate (5-year survival, around 90%). Recently, interest has increased concerning preventing secondary complications (secondary cancer, endocrine disorders) in long-term survivors. We aimed to study the epidemiologic features and therapeutic outcomes of HL in children, adolescents, and young adults in Korea. Methods: We performed a multicenter, retrospective study of 224 patients aged < 25 years diagnosed with HL at 22 participating institutes in Korea from January 2007 to August 2016. Results: A higher percentage of males was diagnosed at a younger age. Nodular sclerosis histopathological HL subtype was most common, followed by mixed cellularity subtype.Eighty-one (36.2%), 101 (45.1%), and 42 (18.8%) patients were classified into low, intermediate, and high-risk groups, respectively. Doxorubicin, bleomycin, vinblastine, dacarbazine was the most common protocol (n = 102, 45.5%). Event-free survival rate was 86.0% ± 2.4%, while five-year overall survival (OS) rate was 96.1% ± 1.4%: 98.7% ± 1.3%, 97.7% ± 1.6%, and 86.5% ± 5.6% in the low, intermediate, and high-risk groups, respectively (P = 0.021). Five-year OS was worse in patients with B-symptoms, stage IV disease, highrisk, splenic involvement, extra-nodal lymphoma, and elevated lactate dehydrogenase level.In multivariate analysis, B-symptoms and extra-nodal involvement were prognostic factors for poor OS. Late complications of endocrine disorders and secondary malignancy were observed in 17 and 6 patients, respectively. Conclusion This is the first study on the epidemiology and treatment outcomes of HL in children, adolescents, and young adults in Korea. Future prospective studies are indicated to develop therapies that minimize treatment toxicity while maximizing cure rates in children, adolescents, and young adults with HL.

OBJECTIVE: To estimate the prevalence of non-adherence to rheumatoid arthritis (RA) medication and identify the associated factors for non-adherence in RA patients. METHODS: Among the KORean Observational study Network for Arthritis 3,523 patients who completed a questionnaire about the adherence to RA medication were analyzed. The patients were divided into two groups: 1) adherent group, patients who skipped medication ≤5 days within the past 2 months; and 2) non-adherent group, patients who skipped ≥6 days of medication. The baseline characteristics were compared, and multivariable regression analysis was performed to identify the associated factors for non-adherence. RESULTS: The non-adherent group had 339 patients (9.6%). The common causes of non-adherence were forgetfulness (45.8%), absence of RA symptoms (24.7%), and discomfort with RA medication (13.1%). Younger age (odds ratio [OR] 1.02, p < 0.01) and higher income (OR 1.70, p < 0.01) were associated with an increased risk of non-adherence. Whereas higher functional disability (OR 0.68, p < 0.01) and oral corticosteroid use (OR 0.73, p=0.02) were associated with a decreased risk of non-adherence. The associated factors differed according to cause of non-adherence. Having adverse events (OR 2.65, p=0.02) was associated with the risk of non-adherence due to discomfort with RA medication while a higher level of education (OR 2.37, p=0.03) was associated with the risk of non-adherence due to an absence of RA symptoms. CONCLUSION: The 9.6% of Korean RA patients were non-adherent to RA medication. The associated factors differed according to the cause of non-adherence. Therefore, an individualized approach will be needed to improve the adherence to RA medication.
Arthritis ; Arthritis, Rheumatoid ; Education ; Humans ; Medication Adherence ; Observational Study ; Prevalence